Selective Discrimination of Key Enzymes of Pathogenic and Non

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Selective Discrimination of Key Enzymes of Pathogenic and Non-Pathogenic Bacteria on Autonomously Reporting Shape-Encoded Hydrogel Patterns Zhiyuan Jia, Issa Sukker, Mareike Müller, and Holger Schönherr ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.7b15147 • Publication Date (Web): 18 Jan 2018 Downloaded from http://pubs.acs.org on January 18, 2018

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ACS Applied Materials & Interfaces

Selective

discrimination

pathogenic

and

of

key

non-pathogenic

enzymes

of

bacteria

on

autonomously reporting shape-encoded hydrogel patterns Zhiyuan Jia, Issa Sukker, Mareike Müller,* and Holger Schönherr* AUTHOR ADDRESS: Physical Chemistry I & Research Center of Micro and Nanochemistry and Engineering (Cμ), Department of Chemistry and Biology, University of Siegen, AdolfReichwein-Straße 2, 57076 Siegen, Germany

KEYWORDS: Hydrogels, Biosensors, Selective Bacteria Detection, Enterohemorrhagic E. Coli (EHEC), Micropatterns

ABSTRACT: This work reports on a new approach to rapidly and selectively detect and discriminate enzymes of pathogenic from those of non-pathogenic bacteria using a patterned autonomously reporting hydrogel on a transparent support, in which the selectivity has been encoded by pattern shape to enable facile detection by a color change at one single wavelength.

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In particular, enzyme-responsive chitosan hydrogel layers that report the presence of the enzymes β-glucuronidase (β-Gus) and β-galactosidase (β-Gal), produced by the non-virulent Escherichia coli K12 (E.coli K12) and the food-borne biosafety level 3 pathogen enterohemorrhagic E. coli (EHEC), respectively, via the blue color of an indigo dye were patterned by two complementary strategies. The comparison of the functionalization of patterned chitosan patches on a solid support with two chromogenic substrates on the one hand and the area selective conjugation of the substrates on the other hand showed that the two characteristic enzymes could indeed be rapidly and selectively discriminated. The limits of detection (LOD) of the highly stable sensing layers for an observation time of 60 minutes using a spectrophotometer correspond to enzyme concentrations of β-Gus and β-Gal of  5 nM and  3 nM, respectively, and to  62 and  33 nM for bare eye detection in non-optimized sensor patches. These results confirm the applicability of this approach, which is compatible with the simple measurement of optical density at one single wavelength only as well as with parallel, multiplexed detection, to differentiate the enzymes secreted by a highly pathogenic E. coli from a non-pathogenic E. coli based on specifically secreted enzymes. Hence a general approach for the rapid and selective detection of enzymes of different bacterial species for potential applications in food safety as well as point of care microbiological diagnostics is described.

Introduction In recent years, a significantly increasing number of incidences of food-borne diseases related to bacterial contaminations in food constitutes a major public health problem all across the globe.1,2 Likewise, after decades of immediate treatment of bacterial infections with antibiotics, which saved many millions of lives, antibiotic resistances are increasing at an alarming rate.3,4,5,6 Hence


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bacterial infections have again become a threat to patients worldwide, also because antibioticresistant bacteria spread rapidly.7 It can be concluded that part of the antibiotics crisis is related to inappropriately prescribed antibiotics that accelerate the rate of resistance build-up in bacteria. 7,8

In this general context, the simple, yet rapid and selective detection of pathogenic bacteria and

bacterial infections is of prime importance to allow for targeted and rapid treatment. 9 For instance, rapid and economically affordable diagnostics may help to differentiate pathogenic bacteria from non-pathogenic bacteria to ensure adequate precautions and treatment. For pathogen detection and identification, there are traditionally standard microbiological procedures based on selective culturing method combined with the quantification of colony forming units (CFU’s). In recent years, polymerase chain reaction (PCR) based procedures have complemented these methods for pathogen detection.10,11 A very recent addition to the screening technologies that are available and approved e.g. by the FDA are mass spectrometric techniques, such as Matrix-assisted Laser Desorption/Ionization Imaging Mass Spectrometry or 3D Imaging (3D) Mass Spectrometry. 12 Although these established methods can provide conclusive and unambiguous results, they required highly trained personnel and are either time consuming, relatively expensive, or may not work properly in remote areas without appropriate electricity or climate control.13 Among the more recently developed alternative methods for bacterial infection sensing, functional nanocapsules (liposomes14,15 and polymersomes16,17) and nanoparticles18,19 as well as sensing films, which detect or differentiate bacteria or bacterial infections at an early stage, have received considerable attention.20,21,22,23,24,25 For instance, the reporter liposomes developed by Jenkins and co-workers could signal infection and discriminate Staphylococcus aureus from Pseudomonas aeruginosa via a released fluorescent reporter dye after the selective break down


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of appropriately designed multicomponent liposomes by bacterial virulence factors.15 A similar approach for sensing high concentrations of bacterial enzymes that differentiate the presence of few bacteria and the onset of infection by enzyme-labile vesicles was realized with enzymelabile amphiphilic block copolymers, as was reported before.16,17 Bacteria detection or differentiation between bacterial species could also be realized with nanoparticles18,19 or sensing films, as mentioned. Wu et al. reported on a highly sensitive and specific multiplexed method to detect three pathogenic bacteria like Staphylococcus aureus, Vibrio parahemolyticus, and Salmonella Typhimurium using multicolor up-conversion nanoparticles (UCNPs).26 For applications that expand the mentioned potential topically applied approaches towards potential use inside patients, a polymer-based pH-responsive sensor system, which could be applied as an early warning system of urinary catheter blockage, was reported by Milo et al.27 Here a pH-responsive polymeric coating within the catheter releases a fluorescent dye upon degradation, which occurs in the presence of Proteus mirabilis infections, providing a visual response. Other methods focus on bacterial enzymes or toxins able to trigger a visible response of sensing devices. For instance, a colorimetric sensor, which is based on a bacteria-specific RNAcleaving DNAzyme probe as the molecular recognition element, has been reported by Tram et al.28 Here the sensing signal has been obtained by an increase in the pH value of the test solution due to the hydrolysis of urea by urease. As an alternative, we have recently reported on autonomously reporting chitosan films that are equipped with different fluorogenic or chromogenic substrates, such as the fluorogenic substrate 4-methylumbelliferyl-β-D-glucuronide and the chromogenic substrates 5-bromo-4chloro-3-indolyl-β-D-glucuronide and 4-nitrophenyl-β-D-glucuronide.21,22,25 These substrates


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were conjugated to chitosan hydrogel film coatings to detect the presence of the characteristic enzyme β-glucuronidase (β-Gus) of E.coli (K 12). Related chitosan-based platforms for the detection and discrimination of different bacterial enzymes to prove the presence of Pseudomonas aeruginosa vs. Staphylococcus aureus on the one hand and non-pathogenic E.coli (K 12) vs. pathogenic E.coli (EHEC) O157:H7, were reported.23,24 In general, the color change of the autonomously reporting hydrogels, resulting from a selective enzymatic cleavage reaction of the corresponding colorimetric substrate, was rapidly detectable (depending on the enzyme and its concentration etc. typically in ≤ 1 h) with very low limits of detection for the enzymes on this observation time scale (in several cases of fluorescence-based detection

Selective Discrimination of Key Enzymes of Pathogenic and Non

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